What things may come

2010 has been a banner year, not only because as a company, Clarabridge has passed many significant milestones, but because sentiment and text analytics have passed from infancy to adulthood over a very short, intense period of time. Market forces have converged to provide us with the opportunity and the means to push sentiment and text analytics into many mainstream applications across a variety of industries. You can see the tangible results in our year end press release, and the rush of interest from the analyst community, with folks like Gartner, Hurwitz’s Fern Halper, Constellation’s Ray Wang, Bruce Temkin, Paul Greenberg all talking about the key role multichannel text and sentiment analytics will play in 2011.

So, that all said, I’ve decided to put out my own predictions for 2011 in the sentiment and text analytics space.

In 2011 expect to see the beginnings of the merging of text analytics and predictive analytics technology stacks. Vendors of text analytics solutions will begin to move beyond looking back, or analyzing the moment, and move into the realm of identifying the predictors of positive outcomes in a campaign, identifying and tracking the drivers of loyalty using advanced predictive models, and using predictive techniques to help prioritize and manage changes to customer experiences. This will happen in a variety of industries including financial services, hospitality, retail, and healthcare industries.

The value of text analytics, especially related to customer experience monitoring, analysis, and action, is amplified when the content being analyzed is sourced from a broad, representative data set of customers. In 2010, while pure play social media monitoring and analysis was exploding across the scene, a small but rapidly growing set of Fortune 1000 organizations began to recognize that multichannel customer analytics, from a wide variety of text based sources (online, offline, call center, and community/survey), provided a much fuller, much more accurate view of customer emotion, customer intent, and loyalty than single source solutions. In 2011 expect to see solutions that fuse multiple channels of customer interaction, engagement, and support to be a dominant growth area for semantic analysis.

Text mining and sentiment analysis is evolving as analysts become more sophisticated and demanding of insights. Over the past few years text analytics solutions focused on “structuring” the unstructured, fusing it with structured data, then on applying industry or domain specific classification models for further refined analysis and investigation, and most recently on instrumenting the data for robust monitoring, analysis, and alerting of past or current conditions. In 2011 expect use cases to continue to be analyst driven and facilitated through a business intelligence (BI) reporting framework, but expect the latency of solutions to decrease, and the automation of insight assessment, delivery, and action to increase. For leading edge users expect to see text analytics solutions assess customer problems and automatically suggest communications to customers, or to automate the recommendations of customer support representatives. In short, look for text analytics to become more “real time” and to become more automated in distilling and disseminating insights.

Vendors of text analytics solutions have typically focused on the 80/20 rule in the past few years – supporting the languages and markets closest to their home bases that provide 80% value for 20% of the effort. But enterprises collect and analyze content from around the world, in many languages, and over time they are demanding that more content from more sources be integrated into their solutions, and that insights be made available to more users across the globe. In 2011 expect to see North American vendors to add European, Latin American and Asian language support to their offerings to expand their business footprints internationally through direct and indirect sales and marketing efforts, and expect to see enterprise applications be deployed across multiple user communities worldwide using localized application interfaces and analytics.

Over the past few years text mining and analytics solutions have not been seamlessly integrated into operational systems or processes. In 2010 a number of vendors started offering robust APIs and frameworks for integrating information into operational systems – CRM, Call Center, Campaign Automation, and Social Media engagement spaces. In 2011 expect to see these operationally integrated solutions come on line from many pioneering solution providers, and to see text insights automatically driving recommendations, actions, or process improvements into operational systems and platforms. Enabling this trend, expect to see partnerships and collaborations between historically analytic vendors and historically transactional vendors in the customer support, customer experience, and customer intelligence spaces. Clarabridge and Verint’s integrated speech/text offering is a leading indicator of creative collaborations to come.

With this all said, what can businesses do to prepare? Invest in voice of the customer pilot programs if you don’t have one, and if you do, invest in bringing in more employees with analytics backgrounds. Look forward, and spend time and money now to understand how all of your systems are going to interact with each other. Put together an action plan. Make your organization customer centric, and the commitment has to be from the top down. Leaders set the tone for how people act and react. Your company culture will define your ability to succeed, so don’t underestimate the value of making sure everyone in the company is focused on listening to the customer.

Data is the present and the future, those who know how to use it, will benefit the most, Knowledge is power is a mantra for a reason.

A Greater Washington Ernst & Young Entrepreneur of the Year in IT services, Sid is the CEO and Co-Founder of Clarabridge™. Sid provides executive leadership and strategic direction and is a well-known expert in customer experience, business intelligence, and text mining.

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